Professorship for Information Systems, in particular Machine Learning
Organisational unit: Professoship
Main research areas
Research
We are interested in statistical machine learning with a focus on spatiotemporal problems, such as user navigation on the web, adaptive testing and adaptive learning environments, and the coordination of football players on the pitch. While we mainly focus on basic research, we also collaborate with selected partners in academia, sports and industry in different projects.
Teaching
Our teaching focuses on introductory/advanced machine learning and data mining as well as basic statistics. We regularly offer courses in the Management & Data Science Master and the Information Systems Bachelor programs. Exemplary courses comprise Deep Learning (Data Science), Statistics (Information Systems), and Machine Learning & Data Mining (Engineering).
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Toward Learning Distributions of Distributions
Wohlstein, M. & Brefeld, U., 2025, In: Proceedings of Machine Learning Research. 265, p. 269-275 7 p.Research output: Journal contributions › Conference article in journal › Research › peer-review
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Uma Caracterização das Polı́ticas de Privacidade Utilizadas em Aplicativos no Brasil
Jardim, G. P. S., Rabello, M. E. R., Lima, A. C., Brefeld, U. & Quadros dos Reis, V., 05.08.2022, Anais do III Workshop sobre as Implicações da Computação na Sociedade (WICS). Sociedade Brasileira de Computação (SBC), p. 13-25 13 p. (WORKSHOP SOBRE AS IMPLICAÇÕES DA COMPUTAÇÃO NA SOCIEDADE (WICS); no. 3/2022).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Universal Threshold Calculation for Fingerprinting Decoders using Mixture Models
Schäfer, M., Mair, S., Berchtold, W. & Steinebach, M., 17.06.2015, Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security. Association for Computing Machinery, Inc, p. 109-114 6 p. (IH and MMSec 2015 - Proceedings of the 2015 ACM Workshop on Information Hiding and Multimedia Security).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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User Authentication via Multifaceted Mouse Movements and Outlier Exposure
Matthiesen, J. J., Hastedt, H. & Brefeld, U., 01.04.2023, Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings. Crémilleux, B., Hess, S. & Nijssen, S. (eds.). Cham: Springer Nature Switzerland AG, p. 300-313 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13876 LNCS).Research output: Contributions to collected editions/works › Article in conference proceedings › Research
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Using Wikipedia for Cross-Language Named Entity Recognition
Fernandes, E. R., Brefeld, U., Blanco, R. & Atserias, J., 2016, Big Data Analytics in the Social and Ubiquitous Context: 5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers. Atzmüller, M., Chin, A., Janssen, F., Schweizer, I. & Trattner, C. (eds.). Springer International Publishing AG, p. 1-25 25 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9546).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Who can receive the pass? A computational model for quantifying availability in soccer
Dick, U., Link, D. & Brefeld, U., 01.05.2022, In: Data Mining and Knowledge Discovery. 36, 3, p. 987-1014 28 p.Research output: Journal contributions › Journal articles › Research › peer-review
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Zur empirischen Beforschung des mBooks Belgien: Die Chancen eines Methodenmix
Schreiber, W., Wagner, W., Trautwein, U. & Brefeld, U., 10.2019, Das Geschichtsschulbuch: Lehren – Lernen – Forschen . Kühberger, C., Bernhard, R. & Bramann, C. (eds.). Münster: Waxmann Verlag, p. 57-80 24 p. (Salzburger Beiträge zur Lehrer/innen/bildung; vol. 6).Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review